Predicting peptides structure with solvation potential and rotamer library dependent of the backbone

In this work, genetic algorithms concepts along with a rotamer library dependent of backbone and implicit solvation potential are used to study the tertiary structure of peptides. We starting from known primary sequence and optimize the structure of the backbone while the side chains allowed adopting the conformations present in a rotamer library. The GA, implemented with two force fields with a growing complexity, was used predict the structure of a polyalanine and a polyisolueucine. This paper presents good and interesting results about the study of peptides structures and about the development of computational tools to study peptides structures.